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4-year studentship: Causal modelling in public health: developing methodology for linkage and analysis of primary and secondary care databases

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4-year studentship: Causal modelling in public health: developing methodology for linkage and analysis of primary and secondary care databases

Δημοσίευση από grstats Την / Το Παρ 2 Μαρ 2012 - 14:48

This 4-year studentship provides full support for tuition fees, all associated research costs and an annual tax-free stipend at minimum Research Council rates (£13,590 in 2011). The project is due to commence October 2012 and is open to UK/EU nationals only due to the nature of the funding.

Project Title: Causal modelling in public health: developing methodology for linkage and analysis of primary and secondary care databases

Project Supervisor(s): Prof Matt Sutton (Health Economics), Dr Richard Emsley (Biostatistics), Dr Will Dixon (Arthritis Research UK Epidemiology Unit)

Institution: Health Sciences Research Group, School of Community Based Medicine at The University of Manchester

Funding Availability: Competition Funded PhD Project (European/UK Students Only)

Application Deadline: Tuesday 06 March 2012

Further information:

Project Outline:

Modern information systems increasingly provide rich datasets on population behaviour and health, with the potential to provide a platform for high quality epidemiological studies to answer critical clinical questions. However, achieving this potential requires effective linkage of data in different contexts, and the development of sophisticated methods to allow rigorous testing of clinical hypotheses. Missing information in one dataset can be supplemented by data from a second source to create an augmented dataset.

This project focuses on developing and implementing methodology for the linkage and analysis of two large complex datasets, one from general practice and one containing patients with rheumatoid arthritis (RA) managed in secondary care. Once linked, the augmented dataset will be used to answer substantive clinical questions relating to the use of biologic therapy in RA patients. For example, can the behaviour of patients on biologic therapy (e.g. discontinuation of therapy) be explained by data collected in primary care (e.g. side effects, concomitant medication)? How does the use of biologic therapy impact on the number of GP consultations? Does biologic therapy lead to more non-serious adverse events such as headaches?

The project will involve developing and applying econometric and statistical methods, particularly related to approaches for linking datasets, longitudinal data analysis and causal inference. Existing methods will be applied to answer the substantive questions, and opportunities for further methodological development pursued in order to develop new models for future analysis.

The successful candidate will obtain skills in biomedical informatics, ehealth, econometrics, linkage and management of complex data sets, and secondary data analysis which are applicable in other disease areas beyond inflammation. Previous PhD graduates from our group have progressed into prestigious postdoctoral positions within biostatistics, health econometrics or epidemiology.

Applicants should hold a minimum upper-second honours degree (or equivalent) in mathematics, statistics, economics or a related area. A Masters in Biostatistics, Epidemiology or Health Economics would be an advantage.

Please direct applications in the following format to Professor Matt Sutton (

. Academic CV
. Official academic transcripts
. Contact details for two suitable referees
. A personal statement (750 words maximum) outlining your suitability for the study, what you hope to achieve from the PhD and your research experience to date.

Any enquiries relating to the project and/or suitability should be directed to Professor Sutton at the address above. Applications are invited up to and including Tuesday 6 March 2012.


Dr Richard Emsley
MRC Research Fellow
Biostatistics, Health Sciences Research Group
School of Community Based Medicine
The University of Manchester
4.304 Jean McFarlane Building
Oxford Road
M13 9PL
0161 306 8002

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